EVALUATING LAND USE CHANGE IN RAPIDLY URBANIZING NIGERIA: CASE STUDY OF YOLA, ADAMAWA STATE

This paper examines the land use change pattern of rapidly developing city of Yola, Nigeria with a view of fmding the explanatory variables for the changes. To achieve this objective, two basic steps are followed: i) land use change detection analysis was performed using Landsat image of 1987 and 2005, ii) a model of land use change pattern was developed using Geographically Weighted Regression (GWR) to estimate the strength of the relationship between land use change and its associated factors. The classification accuracy and kappa statistics of the images are satisfactory. For the 1987 image, the overall classification accuracy of 87.07% and a kappa statistic of 83.37% are observed, whereas, 92.26% (overall accuracy) and 90.41% (kappa statistic) for 2005 were reported. In order to develop the GWR model, several candidate explanatory variables were identified and assessed. The result shows that population, administrative wards, population density, and new layouts are the most important variables that explain the changes. The GWR model result gives a strong Adjusted-R2 of 0.967. While, the Local R-2 values varied spatially ranging from 0.26 to 0.96. The Akaike's Information Criterion (AIC) is (111.14); a smaller value of AICs is fine on local modelling. The spatial patterns of residuals showed some under prediction and over prediction. However, the model exhibits no spatial autoconelation as evidenced by Moran's-I (0.02); this means that the residuals are randomly distributed. The coefficient surface maps indicate how the relationship of each explanatory variable varies across space. Areas with large coefficients indicate the locations where that particular explanatory variable is most important in explaining the depended variable.